performance_equiv {LogRegEquiv} | R Documentation |
This function takes two logistic regression models M_A, M_B
,
test data, significance level \alpha
and acceptable score
degradation \delta_B
. It checks whether the models perform
equivalently on the test set and returns various figures.
performance_equiv(
model_a,
model_b,
test_data,
dv_index,
delta_B = 1.1,
alpha = 0.05
)
model_a |
logistic regression model |
model_b |
logistic regression model |
test_data |
testing dataset |
dv_index |
column number of the dependent variable |
delta_B |
acceptable score degradation (defaults to 1.1) |
alpha |
significance level |
equivalence
Are models M_A,M_B
producing equivalent
Brier scores for the given test data? (boolean)
brier_score_ac
M_A
Brier score on the testing data
brier_score_bc
M_B
Brier score on the testing data
diff_sd_l
SD of the lower Brier difference BS^A-\delta_B^2BS^B
diff_sd_u
SD of the upper Brier difference BS^A-\delta_B^{-2}BS^B
test_stat_l
t_L
equivalence boundary for the test
test_stat_u
t_U
equivalence boundary for the test
crit_val
a level-\alpha
critical value for the test
delta_B
Calculated equivalence parameter
p_value_l
P-value for t_L
p_value_u
P-value for t_U